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HIGGINS Error handling strategies in a spoken dialogue system PowerPoint PPT Presentation


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HIGGINS Error handling strategies in a spoken dialogue system Rolf Carlson, Jens Edlund and Gabriel Skantze. Error handling research issues The long term research goals of the project include these items, which permeate shorter term research issues:

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HIGGINS Error handling strategies in a spoken dialogue system

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Higgins error handling strategies in a spoken dialogue system

HIGGINS

Error handling strategies in a spoken dialogue system

Rolf Carlson, Jens Edlund and Gabriel Skantze

  • Error handling research issues

  • The long term research goals of the project include these items, which permeate shorter term research issues:

  • How do different levels of feedback and detail in system responses affect robustness and efficiency of the dialogue?

  • Which factors should govern the dialogue strategy regarding feedback and information detail?

  • How can the different system modules calculate confidence measures?

  • How can we categorise errors regarding the types of error handling they demand?

  • How should the system act when it doesn't understand, or only partially understands, what the user says?

  • How does the user's beliefs about the system’s understanding correlate to its actual understanding, depending on error handling strategy?

  • The HIGGINS domain

  • The primary domain of HIGGINS is city navigation for pedestrians.

  • Secondarily, HIGGINS is intended to provide simple information about the immediate surroundings.

  • Methods

  • We endeavour to follow these design principles:

  • Versatility

    • The dialogue system is distributed and module based, which makes switches between different system configurations easier.

    • The modules are built to be versatile and it is simple to test different module internal configurations.

  • Empirical iterations

    • Modules are based on experiences drawn from empirical data, when possible.

    • Modules are built to be testable against empirical data.

Scenario

User:I want to go to the closest subway station.

System:Ok, to the closest subway station. Can you describe where you are now?

User: I have an ATM to my left and a pedestrian crossing in front of me.

System:Can you see some trees to your right and a white building in front of you?

User:Yes

System:Ok, take left after the large building which you have on your left and follow the street until you reach a crossing.

User:Ok, there is a bus station here.

System:That’s right. Take left again after the bus station.

  • Current research issues

  • A sample of the issues we are currently working on:

  • Which robust parsing techniques are suitable for more complex utterances?

    • The HIGGINS parser presently achieves robust parsing by using grammars allowing insertions, fragments and non-congruence.

  • How does a dialogue manager that is able to vary its feedback level make its choices?

    • The HIGGINS parser produces confidence measures which may be combined with ASR confidence to provide a basis for selecting feedback level.

  • How can incremental speech recognition be utilised to improve dialogue?

    • The HIGGINS parser supports incremental parsing that facilitates fast feedback, which could help the user detect and correct errors.

  • What demands on interpretation and error handling are specific for the chosen domain?

    • Pedestrian navigation dialogues and human error handling strategies has been collected in a modified Wizard of Oz setting.

    • Spatial descriptions in a simulated 3D environment are currently being collected.

  • Domain challenges

  • The system should be able to:

  • Represent complex properties of objects as well as relations between objects.

  • Make morphological distinctions between singular/plural, definite/indefinite.

  • Engage in a dialogue to find out the user’s destination and then iteratively update a hypothesis of the user’s position based on the user’s descriptions of the surroundings.

  • Compute the user’s position using spatial and temporal reasoning.

  • Engage in an extended dialogue in case the user’s descriptions are insufficient for determining the position.

  • Generate route directions in appropriately sized chunks, providing the optimal path and using grounded concepts in the directions.

http://www.speech.kth.se/higgins/


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